Schedule | AI in Finance Summit NY 2027

Day 1 April 12
Day 2 April 13

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07:30

REGISTRATION & LIGHT BREAKFAST
08:30

Chairperson’s Opening Remarks & Icebreaker
08:40

Beyond RAG: Building the Reasoning Layer for AI in Finance

Harry Mendell - Data Architect Technology Group - FEDERAL RESERVE BANK OF NEW YORK

• Moving beyond retrieval to evidence-based reasoning and financial decision-making.
• Connecting enterprise data, semantics, metrics, and analytics through a unified reasoning architecture.
• Ensuring AI-driven financial insights are accurate, explainable, and auditable
09:10

From Data to Strategy: Transforming Investment Processes with a Self-Correcting Multi-Agent Framework

Matt Goldwasser - Head of AI Data Science - T. ROWE PRICE

• Traditional LLMs Are Not Production-Ready for Regulated Investment Workflows
• Harbor's Multi-Agent AVR Framework Delivers Institutional-Grade Reliability
• Validation-Centric AI Is Essential for Scalable
Adoption
09:40

Quantum Meets AI: Building Hybrid Computing Workflows for Finance

• Identifying financial workloads suited to a combination of AI, classical computing, and quantum methods.
• Designing hybrid workflows that coordinate data preparation, quantum processing, and AI-driven analysis.
• Benchmarking accuracy, execution time, and cost against classical alternatives to assess practical value
10:10

Main Stage Panel Discussion: Protecting Financial Data While Making AI Useful

• How can financial institutions balance data protection with AI innovation?
• What are the biggest security risks when AI accesses sensitive financial data?
• How can organizations prevent data leakage in AI-powered systems and agents?
• What controls are essential for secure AI deployment at scale?
• How can institutions ensure regulatory compliance without limiting AI capabilities?
10:40

Networking Break
11:10

Main Stage
11:10

USE CASES SHOWCASES: Innovative AI Solutions
Explore real-world AI use cases, practical applications, and innovative solutions transforming financial services.
- Innovation Slot 1
- Innovation Slot 2
- Innovation Slot 3
11:40

AI Observability: Can You Monitor a System You Don't Fully Understand?

• How should organizations monitor hallucinations, drift, tool calls, latency and agent behavior in production?
• What metrics actually tell you whether an AI system is safe and performing as expected?
11:40

Main Stage Panel Discussion: Building Trust in Agentic AI for Financial Services: Evidence, Accountability, and Human Oversight

• How can financial institutions ensure AI agents make reliable and explainable decisions?
• What evidence is needed to audit and validate autonomous AI actions?
• Who should be accountable when AI agents make mistakes or cause financial harm?
11:10

Closed-Door Discussion Groups (Invitation Only)
11:10

Discussion Group: Architecting AI-Ready Infrastructure for the Future of Financial Services
11:40

Discussion Group: Security First: Safeguarding Financial Institutions in the Age of AI
11:40

Discussion Group: From Automation to Intelligent Execution: Integrating Agentic AI into Financial Operations

• How can financial institutions ensure AI agents make reliable and explainable decisions?
• What evidence is needed to audit and validate autonomous AI actions?
• Who should be accountable when AI agents make mistakes or cause financial harm?
12:40

Lunch & Networking
01:30

Stage A: AI in Finance Summit
01:30

Panel Discussion: Data Governance for Agentic AI in Finance: From Policies to Real-Time Controls

autonomous agents?
• How can firms enforce data permissions across agent workflows?
• What makes financial data ready for AI agents?
• How can teams trace agent outputs back to source data?
• Which governance controls should run continuously in production?
02:00

How to Optimize Return on Information

Paul-Adrien M - Director, Head of AI - CANTOR FITZGERALD ASSET MANAGEMENT

• Distinguishing data transfer from value-creating data transformation.
• Assigning clear roles to humans, automation, and AI agents.
• Applying lessons from Cantor Fitzgerald Asset Management’s transformation program.
02:30

Discussion Group: Alpha by Design: Multi-Agent AI for Next-Generation Portfolio Management

• Engineering multi-agent systems to combine market signals, research and alternative data
• Using specialized AI agents for portfolio construction, optimization and risk analysis
• Measuring alpha, robustness and decision quality in AI-driven investment strategies
01:30

Stage B: AI in Risk Management for Finance
01:30

Panel Discussion: From Recommendations to Risk Decisions: How Much Autonomy Should AI Have in Finance

• Which risk decisions can AI make autonomously?
• How should institutions test agents before deployment?
• How can AI outputs work alongside rules and risk limits?
• What audit trail ensures traceability and accountability
02:00

Red Teaming AI Agents: How Do You Break a Financial AI Before Attackers Do?

• What are the most dangerous attack surfaces in an agentic architecture?
• Can traditional penetration testing detect AI-specific vulnerabilities?
• How do you test an agent that dynamically changes its own workflow?
• Should financial institutions run continuous adversarial simulations?
02:30

Discussion Group: Building Your AI Audit Trail: A Hands-On Workshop for Continuous Regulatory Assurance

• Capturing end-to-end AI decision and model lineage
• Automating evidence collection for continuous regulatory assurance
• Embedding audit-ready controls into production AI workflows
03:30

Networking Break in Exhibition Area
03:30

The Future AI Workforce: Redesigning Financial Teams for Human + Agent Collaboration

David Micah Katz - Vice President - BLACKROCK (LONDON)

• Defining new roles across humans, copilots and autonomous agents
• Reskilling teams for AI-driven decision-making
• Redesigning performance, accountability and organizational structures
04:00

300 Agents Later: Running AI at Scale in Financial Institutions

Koto Ueda - Head of US Operations / VP of Finance - GENERATIVEX

• Keeping control when hundreds of agents run across the organization: ownership, monitoring and knowing what each one does
• Change management: getting people to use agents in their daily work, so adoption doesn't stall after rollout
• Securing agents in production as their access and autonomy grow
04:30

USE CASE SHOWCASE: Innovative AI Solutions

Explore real-world AI use cases, practical applications, and innovative solutions transforming financial services.
04:40

From Legacy to AI-Ready Finance: Orchestrating Workflows Across Cloud and AI

Girish Gajwani - Vice President of Engineering – Securitized Products - BARCLAYS INVESTMENT BANK

• Modernizing legacy financial systems to support scalable, AI-ready infrastructure.
• Orchestrating intelligent workflows across hybrid cloud and AI environments.
• Moving AI into production while ensuring security, governance, and operational resilience.
05:10

Breaking Financial AI: Adversarial Testing, Model Attacks & Runtime Defense

Dhivya Nagasubramanian - Vice President, AI Transformation & Innovation - U.S. BANK

• Red-team AI agents and uncover hidden vulnerabilities
• Counter prompt injection, model manipulation & data poisoning
• Engineer runtime controls for resilient autonomous systems
05:40

Chair Closing Remarks
05:45

Cocktail Reception & Prize Draw
Private Dinner or After Party

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08:00

Registration & Coffee in the Exhibition Area
08:50

Chairperson’s Opening Remarks & Icebreaker -
09:00

Opening Panel Discussion: Is Your Data Holding Back Your AI Strategy?

• Is your data infrastructure ready for real-time AI workloads?
• How are you improving data quality at enterprise scale?
• How do you connect fragmented data across the financial enterprise?
• How are you governing data without slowing AI development?
• What changes when your data platform moves from analytics to AI?

Panelists:
Kuntal Dutta, Senior Director, Global Head of People Analytics & Workforce Management, BNY
09:30

How We Evaluate AI Applications at a $10 Trillion Asset Manager

Akash Nikam - Head of AI Product & Engineering - VANGUARD

• Assessing AI use cases based on business value, scalability, and measurable ROI.
• Evaluating model performance, reliability, and risks in investment management.
• Establishing governance and evaluation frameworks to move AI applications into production.
10:30

Q-Day Is Coming: Could Quantum Computing Break the Financial System Before Banks Are Ready?

• Exposing vulnerabilities in RSA, ECC, and digital signatures as quantum algorithms challenge financial security.
• Assessing the “harvest now, decrypt later” threat to encrypted transactions, banking data, and financial infrastructure.
• Engineering post-quantum defenses through ML-KEM, hybrid cryptography, and crypto-agile architectures.
11:00

Networking Break
11:30

Main Stage Panel Discussion: The Productivity Measurement Problem: Proving AI’s Financial Value

• What should firms measure beyond employee time saved?
• How do model costs and human review affect returns?
• When does greater productivity create additional capacity or revenue?
• How can teams distinguish AI impact from other improvements?
• What results justify expanding a deployment?
12:00

The Infrastructure Mandate: The Architecture Decision That Will Define Your Next Five Years in Financial Services

• Choosing the right architecture for scalable, AI-native financial services
• Balancing performance, resilience, security and cost at enterprise scale
• Future-proofing infrastructure for AI, data and next-generation workloads
12:30

Keeping Pace with AI: Building Financial Applications That Can Evolve

• How can firms adopt new models without constant rebuilding?
• Which architectural components should remain independent of providers?
• What testing should precede a model upgrade?
• How can teams manage growing integration and maintenance demands?
• When is a new capability worth the disruption of adopting it?
01:00

Lunch & Networking
02:00

Stage A: AI in Finance Summit
02:00

Building Trust in AI - Why Data Quality & Governance Matter Most in Finance

• How does poor data quality directly undermine AI outcomes in finance?
• What governance practices truly build trust in AI-driven decisions?
• How can institutions balance innovation with strict data controls?
• What lessons from early adopters show the ROI of strong data governance?
02:30

From Tools to Talent: Why Your AI Strategy Is Only as Good as Your Operating Model

• Competitive advantage in finance comes from organizational speed, not technology alone
• Designing hybrid human + AI agent teams that create hard-to-replicate capabilities
• Building an AI-native culture as a long-term competitive moat
03:00

Interactive Workshop Session: Real-Time AI Decisioning: From Data Signals to Financial Action

• Architecting real-time AI for fraud, risk, credit and trading
• Moving from batch analytics to continuous decisioning
• Balancing speed, accuracy, explainability and control
02:00

Stage B: AI Foundations & Enterprise Architecture for Financial Services
02:00

From AI Experiments to Enterprise Infrastructure: Architecting the Bank for the Next Wave of AI

• Moving from isolated AI pilots to reusable enterprise platforms
• Modernizing data, compute and application architecture for AI
• Building scalable foundations for production AI across the bank
02:30

Semantic Models Are Infrastructure: Powering Reliable AI at Scale

• Why today’s semantic layer is breaking and silently corrupting both analytics and AI
• How we built a deterministic, versioned semantic control plane (no LLM guesswork)
• Turning semantics into infrastructure that powers both BI and GenAI consistently
03:00

Interactive Workshop Session: The AI Data Plane: Moving Financial Data From Storage to Intelligence

• Real-time data movement for AI workloads
• Vector, transactional and unstructured data architectures
• Reducing the distance between data and inference
03:30

Networking Break in Exhibition Area – Prize Draw & Giveaway
04:00

Can AI Agents Actually Think? Building Financial Systems with Memory & Reasoning

• Memory turns AI from reactive to strategic
• Reasoning is the edge—prediction alone is not enough
• Smarter agents make higher-stakes financial decisions
• The real challenge: trusted memory, controlled reasoning
04:30

AI Orchestration: Connecting Models, Agents, APIs & Core Banking Systems

• Orchestrating AI models and agents across complex financial ecosystems
• Connecting agents to APIs, data platforms and core banking systems
• Managing real-time workflows, latency and system interoperability
• Building secure, scalable orchestration layers for production AI in finance
05:00

Chair Closing Remarks

• Real-time data movement for AI workloads
• Vector, transactional and unstructured data architectures
• Reducing the distance between data and inference

AI in Finance Summit NY schedule

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